diff --git a/.gitignore b/.gitignore
index 4046166..67eceef 100644
--- a/.gitignore
+++ b/.gitignore
@@ -170,3 +170,5 @@ cython_debug/
 
 *.mp4
 *.mkv
+
+/cccv/cache_models/
diff --git a/README.md b/README.md
index f63bc63..bc48edd 100644
--- a/README.md
+++ b/README.md
@@ -20,7 +20,7 @@ pip install cccv
 
 ### Start
 
-#### cv2
+#### Load a registered model in cccv
 
 a simple example to use the SISR (Single Image Super-Resolution) model to process an image
 
@@ -37,6 +37,22 @@ img = model.inference_image(img)
 cv2.imwrite("test_out.jpg", img)
 ```
 
+#### Load a custom model from remote repository or local path
+
+a simple example to use [remote repository](https://github.com/EutropicAI/cccv_demo_remote_model) or local path, auto register the model then load
+
+```python
+import cv2
+import numpy as np
+
+from cccv import AutoModel, SRBaseModel
+
+# remote repo
+model: SRBaseModel = AutoModel.from_pretrained("https://github.com/EutropicAI/cccv_demo_remote_model")
+# local path
+model: SRBaseModel = AutoModel.from_pretrained("/path/to/cccv_demo_model")
+```
+
 #### VapourSynth
 
 a simple example to use the VapourSynth to process a video
diff --git a/cccv/__init__.py b/cccv/__init__.py
index 7a602b2..91d0965 100644
--- a/cccv/__init__.py
+++ b/cccv/__init__.py
@@ -26,6 +26,6 @@
 
 from cccv.arch import ARCH_REGISTRY
 from cccv.auto import AutoConfig, AutoModel
-from cccv.config import CONFIG_REGISTRY, BaseConfig, SRBaseConfig, VFIBaseConfig, VSRBaseConfig
+from cccv.config import CONFIG_REGISTRY, AutoBaseConfig, BaseConfig, SRBaseConfig, VFIBaseConfig, VSRBaseConfig
 from cccv.model import MODEL_REGISTRY, AuxiliaryBaseModel, CCBaseModel, SRBaseModel, VFIBaseModel, VSRBaseModel
 from cccv.type import ArchType, BaseModelInterface, ConfigType, ModelType
diff --git a/cccv/arch/sr/dat_arch.py b/cccv/arch/sr/dat_arch.py
index ed65e2b..5eec59f 100644
--- a/cccv/arch/sr/dat_arch.py
+++ b/cccv/arch/sr/dat_arch.py
@@ -365,8 +365,7 @@ def __init__(
         elif idx == 1:
             W_sp, H_sp = self.split_size[0], self.split_size[1]
         else:
-            print("ERROR MODE", idx)
-            exit(0)
+            raise ValueError(f"[CCCV] ERROR MODE: invalid idx {idx}, expected 0 or 1")
         self.H_sp = H_sp
         self.W_sp = W_sp
 
diff --git a/cccv/arch/sr/upcunet_arch.py b/cccv/arch/sr/upcunet_arch.py
index 56aa39e..af702aa 100644
--- a/cccv/arch/sr/upcunet_arch.py
+++ b/cccv/arch/sr/upcunet_arch.py
@@ -376,8 +376,7 @@ def forward(self, x, tile_mode, cache_mode, alpha, pro):
             t2 = tile_mode * 2
             crop_size = (((h0 - 1) // t2 * t2 + t2) // tile_mode, ((w0 - 1) // t2 * t2 + t2) // tile_mode)
         else:
-            print("tile_mode config error")
-            os._exit(233)
+            raise ValueError("[CCCV] tile_mode config error: invalid tile_mode value")
 
         ph = ((h0 - 1) // crop_size[0] + 1) * crop_size[0]
         pw = ((w0 - 1) // crop_size[1] + 1) * crop_size[1]
@@ -526,8 +525,7 @@ def forward_gap_sync(self, x, tile_mode, alpha, pro):
             t2 = tile_mode * 2
             crop_size = (((h0 - 1) // t2 * t2 + t2) // tile_mode, ((w0 - 1) // t2 * t2 + t2) // tile_mode)
         else:
-            print("tile_mode config error")
-            os._exit(233)
+            raise ValueError("[CCCV] tile_mode config error: invalid tile_mode value")
         ph = ((h0 - 1) // crop_size[0] + 1) * crop_size[0]
         pw = ((w0 - 1) // crop_size[1] + 1) * crop_size[1]
         x = F.pad(x, (18, 18 + pw - w0, 18, 18 + ph - h0), "reflect")
@@ -767,8 +765,7 @@ def forward(self, x, tile_mode, cache_mode, alpha, pro):
             t4 = tile_mode * 4
             crop_size = (((h0 - 1) // t4 * t4 + t4) // tile_mode, ((w0 - 1) // t4 * t4 + t4) // tile_mode)
         else:
-            print("tile_mode config error")
-            os._exit(233)
+            raise ValueError("[CCCV] tile_mode config error: invalid tile_mode value")
         ph = ((h0 - 1) // crop_size[0] + 1) * crop_size[0]
         pw = ((w0 - 1) // crop_size[1] + 1) * crop_size[1]
         x = F.pad(x, (14, 14 + pw - w0, 14, 14 + ph - h0), "reflect")
@@ -916,8 +913,7 @@ def forward_gap_sync(self, x, tile_mode, alpha, pro):
             t4 = tile_mode * 4
             crop_size = (((h0 - 1) // t4 * t4 + t4) // tile_mode, ((w0 - 1) // t4 * t4 + t4) // tile_mode)
         else:
-            print("tile_mode config error")
-            os._exit(233)
+            raise ValueError("[CCCV] tile_mode config error: invalid tile_mode value")
         ph = ((h0 - 1) // crop_size[0] + 1) * crop_size[0]
         pw = ((w0 - 1) // crop_size[1] + 1) * crop_size[1]
         x = F.pad(x, (14, 14 + pw - w0, 14, 14 + ph - h0), "reflect")
@@ -1162,8 +1158,7 @@ def forward(self, x, tile_mode, cache_mode, alpha, pro):
             t2 = tile_mode * 2
             crop_size = (((h0 - 1) // t2 * t2 + t2) // tile_mode, ((w0 - 1) // t2 * t2 + t2) // tile_mode)
         else:
-            print("tile_mode config error")
-            os._exit(233)
+            raise ValueError("[CCCV] tile_mode config error: invalid tile_mode value")
         ph = ((h0 - 1) // crop_size[0] + 1) * crop_size[0]
         pw = ((w0 - 1) // crop_size[1] + 1) * crop_size[1]
         x = F.pad(x, (19, 19 + pw - w0, 19, 19 + ph - h0), "reflect")
@@ -1323,8 +1318,7 @@ def forward_gap_sync(self, x, tile_mode, alpha, pro):
             t2 = tile_mode * 2
             crop_size = (((h0 - 1) // t2 * t2 + t2) // tile_mode, ((w0 - 1) // t2 * t2 + t2) // tile_mode)  # 5.6G
         else:
-            print("tile_mode config error")
-            os._exit(233)
+            raise ValueError("[CCCV] tile_mode config error: invalid tile_mode value")
         ph = ((h0 - 1) // crop_size[0] + 1) * crop_size[0]
         pw = ((w0 - 1) // crop_size[1] + 1) * crop_size[1]
         x = F.pad(x, (19, 19 + pw - w0, 19, 19 + ph - h0), "reflect")
diff --git a/cccv/arch/vfi/drba_arch.py b/cccv/arch/vfi/drba_arch.py
index a4c27ee..fa57fb2 100644
--- a/cccv/arch/vfi/drba_arch.py
+++ b/cccv/arch/vfi/drba_arch.py
@@ -1,4 +1,6 @@
 # type: ignore
+import warnings
+
 import numpy as np
 import torch
 import torch.nn as nn
@@ -61,7 +63,7 @@ def inference(self, x, timestep=0.5, scale_list=None, fastmode=True, ensemble=Fa
                     torch.cat((img0[:, :3], img1[:, :3], f0, f1, timestep), 1), None, scale=scale_list[i]
                 )
                 if ensemble:
-                    print("warning: ensemble is not supported since RIFEv4.21")
+                    warnings.warn("[CCCV] ensemble is not supported since RIFEv4.21", stacklevel=2)
             else:
                 wf0 = warp(f0, flow[:, :2])
                 wf1 = warp(f1, flow[:, 2:4])
@@ -71,7 +73,7 @@ def inference(self, x, timestep=0.5, scale_list=None, fastmode=True, ensemble=Fa
                     scale=scale_list[i],
                 )
                 if ensemble:
-                    print("warning: ensemble is not supported since RIFEv4.21")
+                    warnings.warn("[CCCV] ensemble is not supported since RIFEv4.21", stacklevel=2)
                 else:
                     mask = m0
                 flow = flow + fd
@@ -83,7 +85,7 @@ def inference(self, x, timestep=0.5, scale_list=None, fastmode=True, ensemble=Fa
         mask = torch.sigmoid(mask)
         merged[4] = warped_img0 * mask + warped_img1 * (1 - mask)
         if not fastmode:
-            print("contextnet is removed")
+            warnings.warn("[CCCV] contextnet is removed", stacklevel=2)
             """
             c0 = self.contextnet(img0, flow[:, :2])
             c1 = self.contextnet(img1, flow[:, 2:4])
diff --git a/cccv/arch/vfi/ifnet_arch.py b/cccv/arch/vfi/ifnet_arch.py
index 3d7ab51..40087a3 100644
--- a/cccv/arch/vfi/ifnet_arch.py
+++ b/cccv/arch/vfi/ifnet_arch.py
@@ -1,4 +1,6 @@
 # type: ignore
+import warnings
+
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
@@ -43,7 +45,7 @@ def forward(self, x, timestep=0.5, scale_list=None, fastmode=True, ensemble=Fals
                     torch.cat((img0[:, :3], img1[:, :3], f0, f1, timestep), 1), None, scale=scale_list[i]
                 )
                 if ensemble:
-                    print("warning: ensemble is not supported since RIFEv4.21")
+                    warnings.warn("[CCCV] ensemble is not supported since RIFEv4.21", stacklevel=2)
             else:
                 wf0 = warp(f0, flow[:, :2])
                 wf1 = warp(f1, flow[:, 2:4])
@@ -53,7 +55,7 @@ def forward(self, x, timestep=0.5, scale_list=None, fastmode=True, ensemble=Fals
                     scale=scale_list[i],
                 )
                 if ensemble:
-                    print("warning: ensemble is not supported since RIFEv4.21")
+                    warnings.warn("[CCCV] ensemble is not supported since RIFEv4.21", stacklevel=2)
                 else:
                     mask = m0
                 flow = flow + fd
@@ -65,7 +67,7 @@ def forward(self, x, timestep=0.5, scale_list=None, fastmode=True, ensemble=Fals
         mask = torch.sigmoid(mask)
         merged[4] = warped_img0 * mask + warped_img1 * (1 - mask)
         if not fastmode:
-            print("contextnet is removed")
+            warnings.warn("[CCCV] contextnet is removed", stacklevel=2)
             """
             c0 = self.contextnet(img0, flow[:, :2])
             c1 = self.contextnet(img1, flow[:, 2:4])
diff --git a/cccv/arch/vfi/vfi_utils/softsplat.py b/cccv/arch/vfi/vfi_utils/softsplat.py
index 5f82e98..823d523 100644
--- a/cccv/arch/vfi/vfi_utils/softsplat.py
+++ b/cccv/arch/vfi/vfi_utils/softsplat.py
@@ -61,7 +61,7 @@ def cuda_kernel(strFunction: str, strKernel: str, objVariables: typing.Dict):
             strKey += str(objValue.stride())
 
         elif True:
-            print(strVariable, type(objValue))
+            print(f"[CCCV] {strVariable}, {type(objValue)}")
 
         # end
     # end
@@ -106,10 +106,10 @@ def cuda_kernel(strFunction: str, strKernel: str, objVariables: typing.Dict):
                 strKernel = strKernel.replace("{{type}}", "long")
 
             elif isinstance(objValue, torch.Tensor):
-                print(strVariable, objValue.dtype)
+                print(f"[CCCV] {strVariable}, {objValue.dtype}")
 
             elif True:
-                print(strVariable, type(objValue))
+                print(f"[CCCV] {strVariable}, {type(objValue)}")
 
             # end
         # end
diff --git a/cccv/auto/config.py b/cccv/auto/config.py
index e625835..c7e055b 100644
--- a/cccv/auto/config.py
+++ b/cccv/auto/config.py
@@ -1,32 +1,87 @@
+import importlib.util
+import json
+import warnings
+from pathlib import Path
 from typing import Any, Optional, Union
 
-from cccv.config import CONFIG_REGISTRY, BaseConfig
+from cccv.config import CONFIG_REGISTRY, AutoBaseConfig
 from cccv.type import ConfigType
+from cccv.util.remote import git_clone
 
 
 class AutoConfig:
     @staticmethod
     def from_pretrained(
-        pretrained_model_name: Union[ConfigType, str],
+        pretrained_model_name_or_path: Union[ConfigType, str, Path],
+        *,
+        model_dir: Optional[Union[Path, str]] = None,
         **kwargs: Any,
     ) -> Any:
         """
-        Get a config instance of a pretrained model configuration.
+        Get a config instance of a pretrained model configuration, can be a registered config name or a local path or a git url.
 
-        :param pretrained_model_name: The name of the pretrained model configuration
+        :param pretrained_model_name_or_path:
+        :param model_dir: The path to cache the downloaded model configuration. Should be a full path. If None, use default cache path.
         :return:
         """
-        return CONFIG_REGISTRY.get(pretrained_model_name)
+        if "pretrained_model_name" in kwargs:
+            warnings.warn(
+                "[CCCV] 'pretrained_model_name' is deprecated, please use 'pretrained_model_name_or_path' instead.",
+                DeprecationWarning,
+                stacklevel=2,
+            )
+            pretrained_model_name_or_path = kwargs.pop("pretrained_model_name")
 
-    @staticmethod
-    def register(config: Union[BaseConfig, Any], name: Optional[str] = None) -> None:
-        """
-        Register the given config class instance under the name BaseConfig.name or the given name.
-        Can be used as a function call. See docstring of this class for usage.
+        # 1. check if it's a registered config name, early return if found
+        if isinstance(pretrained_model_name_or_path, ConfigType):
+            pretrained_model_name_or_path = pretrained_model_name_or_path.value
+        if str(pretrained_model_name_or_path) in CONFIG_REGISTRY:
+            return CONFIG_REGISTRY.get(str(pretrained_model_name_or_path))
 
-        :param config: The config class instance to register
-        :param name: The name to register the config class instance under. If None, use BaseConfig.name
-        :return:
-        """
-        # used as a function call
-        CONFIG_REGISTRY.register(obj=config, name=name)
+        # 2. check is a url or not, if it's a url, git clone it to model_dir then replace pretrained_model_name_or_path with the local path (Path)
+        if str(pretrained_model_name_or_path).startswith("http"):
+            pretrained_model_name_or_path = git_clone(
+                git_url=str(pretrained_model_name_or_path),
+                model_dir=model_dir,
+                **kwargs,
+            )
+
+        # 3. check if it's a real path
+        dir_path = Path(str(pretrained_model_name_or_path))
+
+        if not dir_path.exists() or not dir_path.is_dir():
+            raise ValueError(f"[CCCV] model configuration '{dir_path}' is not a valid config name or path")
+
+        # load config,json from the directory
+        config_path = dir_path / "config.json"
+        # check if config.json exists
+        if not config_path.exists():
+            raise FileNotFoundError(f"[CCCV] no valid config.json not found in {dir_path}")
+
+        with open(config_path, "r", encoding="utf-8") as f:
+            config_dict = json.load(f)
+
+        for k in ["arch", "model", "name"]:
+            if k not in config_dict:
+                raise KeyError(
+                    f"[CCCV] no key '{k}' in config.json in {dir_path}, you should provide a valid config.json contain a key '{k}'"
+                )
+
+        # auto import all .py files in the directory to register the arch, model and config
+        try:
+            for py_file in dir_path.glob("*.py"):
+                spec = importlib.util.spec_from_file_location(py_file.stem, py_file)
+                if spec is None or spec.loader is None:
+                    continue
+                module = importlib.util.module_from_spec(spec)
+                spec.loader.exec_module(module)
+        except Exception as e:
+            raise ImportError(f"[CCCV] failed register model from {dir_path}, error: {e}, please check your .py files")
+
+        if "path" not in config_dict or config_dict["path"] is None or config_dict["path"] == "":
+            # add the path to the config_dict
+            config_dict["path"] = str(dir_path / config_dict["name"])
+
+        # convert config_dict to pydantic model
+        cfg = AutoBaseConfig.model_validate(config_dict)
+        return cfg
diff --git a/cccv/auto/model.py b/cccv/auto/model.py
index b6d0885..6fd5f4e 100644
--- a/cccv/auto/model.py
+++ b/cccv/auto/model.py
@@ -1,8 +1,10 @@
+from pathlib import Path
 from typing import Any, Optional, Tuple, Union
 
 import torch
 
-from cccv.config import CONFIG_REGISTRY, BaseConfig
+from cccv.auto.config import AutoConfig
+from cccv.config import BaseConfig
 from cccv.model import MODEL_REGISTRY
 from cccv.type import ConfigType
 
@@ -10,7 +12,8 @@
 class AutoModel:
     @staticmethod
     def from_pretrained(
-        pretrained_model_name: Union[ConfigType, str],
+        pretrained_model_name_or_path: Union[ConfigType, str, Path],
+        *,
         device: Optional[torch.device] = None,
         fp16: bool = True,
         compile: bool = False,
@@ -18,14 +21,14 @@ def from_pretrained(
         tile: Optional[Tuple[int, int]] = (128, 128),
         tile_pad: int = 8,
         pad_img: Optional[Tuple[int, int]] = None,
-        model_dir: Optional[str] = None,
+        model_dir: Optional[Union[Path, str]] = None,
         gh_proxy: Optional[str] = None,
         **kwargs: Any,
     ) -> Any:
         """
-        Get a model instance from a pretrained model name.
+        Get a model instance from a registered config name or a local path or a git url.
 
-        :param pretrained_model_name: The name of the pretrained model. It should be registered in CONFIG_REGISTRY.
+        :param pretrained_model_name_or_path:
         :param device: inference device
         :param fp16: use fp16 precision or not
         :param compile: use torch.compile or not
@@ -37,8 +40,8 @@ def from_pretrained(
         :param gh_proxy: The proxy for downloading from github release. Example: https://github.abskoop.workers.dev/
         :return:
         """
+        config = AutoConfig.from_pretrained(pretrained_model_name_or_path, model_dir=model_dir, **kwargs)
 
-        config = CONFIG_REGISTRY.get(pretrained_model_name)
         return AutoModel.from_config(
             config=config,
             device=device,
@@ -56,6 +59,7 @@ def from_pretrained(
     @staticmethod
     def from_config(
         config: Union[BaseConfig, Any],
+        *,
         device: Optional[torch.device] = None,
         fp16: bool = True,
         compile: bool = False,
@@ -63,14 +67,14 @@ def from_config(
         tile: Optional[Tuple[int, int]] = (128, 128),
         tile_pad: int = 8,
         pad_img: Optional[Tuple[int, int]] = None,
-        model_dir: Optional[str] = None,
+        model_dir: Optional[Union[Path, str]] = None,
         gh_proxy: Optional[str] = None,
         **kwargs: Any,
     ) -> Any:
         """
         Get a model instance from a config.
 
-        :param config: The config object. It should be registered in CONFIG_REGISTRY.
+        :param config: The config object. We suggest use cccv.BaseConfig or its subclass.
         :param device: inference device
         :param fp16: use fp16 precision or not
         :param compile: use torch.compile or not
@@ -99,29 +103,3 @@ def from_config(
         )
 
         return model
-
-    @staticmethod
-    def register(obj: Optional[Any] = None, name: Optional[str] = None) -> Any:
-        """
-        Register the given object under the name `obj.__name__` or the given name.
-        Can be used as either a decorator or not. See docstring of this class for usage.
-
-        :param obj: The object to register. If None, this is being used as a decorator.
-        :param name: The name to register the object under. If None, use `obj.__name__`.
-        :return:
-        """
-        if obj is None:
-            # used as a decorator
-            def deco(func_or_class: Any) -> Any:
-                _name = name
-                if _name is None:
-                    _name = func_or_class.__name__
-                MODEL_REGISTRY.register(obj=func_or_class, name=_name)
-                return func_or_class
-
-            return deco
-
-        # used as a function call
-        if name is None:
-            name = obj.__name__
-        MODEL_REGISTRY.register(obj=obj, name=name)
diff --git a/cccv/cache_models/__init__.py b/cccv/cache_models/__init__.py
deleted file mode 100644
index f05df63..0000000
--- a/cccv/cache_models/__init__.py
+++ /dev/null
@@ -1,118 +0,0 @@
-import hashlib
-import os
-import sys
-from pathlib import Path
-from typing import Any, Optional
-
-from tenacity import retry, stop_after_attempt, stop_after_delay, wait_random
-from torch.hub import download_url_to_file
-
-from cccv.config import BaseConfig
-
-if getattr(sys, "frozen", False):
-    # frozen
-    _IS_FROZEN_ = True
-    CACHE_PATH = Path(sys.executable).parent.absolute() / "cache_models"
-    if not CACHE_PATH.exists():
-        os.makedirs(CACHE_PATH)
-else:
-    # unfrozen
-    _IS_FROZEN_ = False
-    CACHE_PATH = Path(__file__).resolve().parent.absolute()
-
-
-def get_file_sha256(file_path: str, blocksize: int = 1 << 20) -> str:
-    sha256 = hashlib.sha256()
-    with open(file_path, "rb") as f:
-        while True:
-            data = f.read(blocksize)
-            if not data:
-                break
-            sha256.update(data)
-    return sha256.hexdigest()
-
-
-def load_file_from_url(
-    config: BaseConfig,
-    force_download: bool = False,
-    progress: bool = True,
-    model_dir: Optional[str] = None,
-    gh_proxy: Optional[str] = None,
-    **kwargs: Any,
-) -> str:
-    """
-    Load file form http url, will download models if necessary.
-
-    Reference: https://github.com/1adrianb/face-alignment/blob/master/face_alignment/utils.py
-
-    :param config: The config object.
-    :param force_download: Whether to force download the file.
-    :param progress: Whether to show the download progress.
-    :param model_dir: The path to save the downloaded model. Should be a full path. If None, use default cache path.
-    :param gh_proxy: The proxy for downloading from github release. Example: https://github.abskoop.workers.dev/
-    :return:
-    """
-
-    CCCV_REMOTE_MODEL_ZOO = os.environ.get(
-        "CCCV_REMOTE_MODEL_ZOO", "https://github.com/EutropicAI/cccv/releases/download/model_zoo/"
-    )
-    CCCV_CACHE_MODEL_DIR = os.environ.get("CCCV_CACHE_MODEL_DIR", str(CACHE_PATH))
-
-    if model_dir is None:
-        model_dir = str(CCCV_CACHE_MODEL_DIR)
-        print(
-            f"[CCCV] Using default cache model path {model_dir}, override it by setting environment variable CCCV_CACHE_MODEL_DIR"
-        )
-
-    cached_file_path = os.path.abspath(os.path.join(model_dir, config.name))
-
-    if config.url is not None:
-        _url: str = str(config.url)
-    else:
-        print(
-            f"[CCCV] Fetching models from {CCCV_REMOTE_MODEL_ZOO}, override it by setting environment variable CCCV_REMOTE_MODEL_ZOO"
-        )
-        if not CCCV_REMOTE_MODEL_ZOO.endswith("/"):
-            CCCV_REMOTE_MODEL_ZOO += "/"
-        _url = CCCV_REMOTE_MODEL_ZOO + config.name
-
-    _gh_proxy = gh_proxy
-    if _gh_proxy is not None and _url.startswith("https://github.com"):
-        if not _gh_proxy.endswith("/"):
-            _gh_proxy += "/"
-        _url = _gh_proxy + _url
-
-    if not os.path.exists(cached_file_path) or force_download:
-        if _gh_proxy is not None:
-            print(f"[CCCV] Using github proxy: {_gh_proxy}")
-        print(f"[CCCV] Downloading: {_url} to {cached_file_path}\n")
-
-        @retry(wait=wait_random(min=3, max=5), stop=stop_after_delay(10) | stop_after_attempt(30))
-        def _download() -> None:
-            try:
-                download_url_to_file(url=_url, dst=cached_file_path, hash_prefix=None, progress=progress)
-            except Exception as e:
-                print(f"[CCCV] Download failed: {e}, retrying...")
-                raise e
-
-        _download()
-
-    if config.hash is not None:
-        get_hash = get_file_sha256(cached_file_path)
-        if get_hash != config.hash:
-            raise ValueError(
-                f"[CCCV] File {cached_file_path} hash mismatched with config hash {config.hash}, compare with {get_hash}"
-            )
-
-    return cached_file_path
-
-
-if __name__ == "__main__":
-    # get all model files sha256
-    for root, _, files in os.walk(CACHE_PATH):
-        for file in files:
-            if not file.endswith(".pth") and not file.endswith(".pt"):
-                continue
-            file_path = os.path.join(root, file)
-            name = os.path.basename(file_path)
-            print(f"[CCCV] {name}: {get_file_sha256(file_path)}")
diff --git a/cccv/config/__init__.py b/cccv/config/__init__.py
index 283a196..4c43937 100644
--- a/cccv/config/__init__.py
+++ b/cccv/config/__init__.py
@@ -3,7 +3,7 @@
 
 CONFIG_REGISTRY: RegistryConfigInstance = RegistryConfigInstance("CONFIG")
 
-from cccv.config.base_config import BaseConfig, SRBaseConfig, VSRBaseConfig, VFIBaseConfig
+from cccv.config.base_config import BaseConfig, SRBaseConfig, VSRBaseConfig, VFIBaseConfig, AutoBaseConfig
 
 # Auxiliary Network
 
diff --git a/cccv/config/base_config.py b/cccv/config/base_config.py
index e34b75f..03c0d02 100644
--- a/cccv/config/base_config.py
+++ b/cccv/config/base_config.py
@@ -1,6 +1,6 @@
 from typing import Optional, Union
 
-from pydantic import BaseModel, FilePath, HttpUrl
+from pydantic import BaseModel, ConfigDict, FilePath, HttpUrl
 
 from cccv.type.arch import ArchType
 from cccv.type.model import ModelType
@@ -15,6 +15,10 @@ class BaseConfig(BaseModel):
     model: Union[ModelType, str]
 
 
+class AutoBaseConfig(BaseConfig):
+    model_config = ConfigDict(extra="allow")
+
+
 class AuxiliaryBaseConfig(BaseConfig):
     pass
 
diff --git a/cccv/config/sr/srcnn_config.py b/cccv/config/sr/srcnn_config.py
index 7d04f11..1a6403b 100644
--- a/cccv/config/sr/srcnn_config.py
+++ b/cccv/config/sr/srcnn_config.py
@@ -6,7 +6,7 @@
 
 
 class SRCNNConfig(SRBaseConfig):
-    arch: ArchType = ArchType.SRCNN
+    arch: Union[ArchType, str] = ArchType.SRCNN
     model: Union[ModelType, str] = ModelType.SRBaseModel
     scale: int = 2
     num_channels: int = 1
diff --git a/cccv/model/base_model.py b/cccv/model/base_model.py
index 7c6b333..9c879eb 100644
--- a/cccv/model/base_model.py
+++ b/cccv/model/base_model.py
@@ -1,14 +1,16 @@
 import sys
+import warnings
 from inspect import signature
-from typing import Any, Optional, Tuple
+from pathlib import Path
+from typing import Any, Optional, Tuple, Union
 
 import torch
 
 from cccv.arch import ARCH_REGISTRY
-from cccv.cache_models import load_file_from_url
 from cccv.config import BaseConfig
 from cccv.type import BaseModelInterface
 from cccv.util.device import DEFAULT_DEVICE
+from cccv.util.remote import load_file_from_url
 
 
 class CCBaseModel(BaseModelInterface):
@@ -37,7 +39,7 @@ def __init__(
         tile: Optional[Tuple[int, int]] = (128, 128),
         tile_pad: int = 8,
         pad_img: Optional[Tuple[int, int]] = None,
-        model_dir: Optional[str] = None,
+        model_dir: Optional[Union[Path, str]] = None,
         gh_proxy: Optional[str] = None,
         **kwargs: Any,
     ) -> None:
@@ -56,7 +58,7 @@ def __init__(
         self.tile: Optional[Tuple[int, int]] = tile
         self.tile_pad: int = tile_pad
         self.pad_img: Optional[Tuple[int, int]] = pad_img
-        self.model_dir: Optional[str] = model_dir
+        self.model_dir: Optional[Union[Path, str]] = model_dir
         self.gh_proxy: Optional[str] = gh_proxy
 
         # post-hook: edit parameters here if needed
@@ -72,7 +74,7 @@ def __init__(
             try:
                 self.model = self.model.half()
             except Exception as e:
-                print(f"[CCCV] Warning: {e}. \nfp16 is not supported on this model, fallback to fp32.")
+                warnings.warn(f"[CCCV] {e}. fp16 is not supported on this model, fallback to fp32.", stacklevel=2)
                 self.fp16 = False
                 self.model = self.load_model()
 
@@ -86,7 +88,7 @@ def __init__(
                         self.compile_backend = "inductor"
                 self.model = torch.compile(self.model, backend=self.compile_backend)
             except Exception as e:
-                print(f"[CCCV] Error: {e}, compile is not supported on this model.")
+                warnings.warn(f"[CCCV] {e}, compile is not supported on this model.", stacklevel=2)
 
     def post_init_hook(self) -> None:
         """
@@ -105,14 +107,14 @@ def get_state_dict(self) -> Any:
         cfg: BaseConfig = self.config
 
         if cfg.path is not None:
-            state_dict_path = str(cfg.path)
+            state_dict_path = cfg.path
         else:
             try:
                 state_dict_path = load_file_from_url(
                     config=cfg, force_download=False, model_dir=self.model_dir, gh_proxy=self.gh_proxy
                 )
             except Exception as e:
-                print(f"[CCCV] Error: {e}, try force download the model...")
+                warnings.warn(f"[CCCV] Error: {e}, try force download the model...", stacklevel=2)
                 state_dict_path = load_file_from_url(
                     config=cfg, force_download=True, model_dir=self.model_dir, gh_proxy=self.gh_proxy
                 )
diff --git a/cccv/util/device.py b/cccv/util/device.py
index e1532a5..92894ae 100644
--- a/cccv/util/device.py
+++ b/cccv/util/device.py
@@ -1,4 +1,5 @@
 import sys
+import warnings
 
 import torch
 
@@ -10,7 +11,7 @@ def default_device() -> torch.device:
         try:
             return torch.device("mps" if torch.backends.mps.is_available() else "cpu")
         except Exception as e:
-            print(f"[CCCV] Error: {e}, MPS is not available, use CPU instead.")
+            warnings.warn(f"[CCCV] {e}, MPS is not available, use CPU instead.", stacklevel=2)
             return torch.device("cpu")
 
 
diff --git a/cccv/util/registry.py b/cccv/util/registry.py
index c160600..ff6c3a9 100644
--- a/cccv/util/registry.py
+++ b/cccv/util/registry.py
@@ -41,7 +41,7 @@ def __init__(self, name: str) -> None:
 
     def _do_register(self, name: str, obj: Any) -> None:
         if name in self._obj_map:
-            print("[CCCV] An object named '{}' was already registered in '{}' registry!".format(name, self._name))
+            raise KeyError(f"[CCCV] An object named '{name}' was already registered in '{self._name}' registry!")
         else:
             self._obj_map[name] = obj
 
@@ -69,7 +69,7 @@ def deco(func_or_class: Any) -> Any:
     def get(self, name: str) -> Any:
         ret = self._obj_map.get(name)
         if ret is None:
-            raise KeyError("[CCCV] No object named '{}' found in '{}' registry!".format(name, self._name))
+            raise KeyError(f"[CCCV] No object named '{name}' found in '{self._name}' registry!")
         return ret
 
     def __contains__(self, name: str) -> bool:
diff --git a/cccv/util/remote.py b/cccv/util/remote.py
new file mode 100644
index 0000000..1598726
--- /dev/null
+++ b/cccv/util/remote.py
@@ -0,0 +1,173 @@
+import hashlib
+import os
+import shutil
+import subprocess
+import sys
+import warnings
+from pathlib import Path
+from typing import Any, Optional, Union
+
+from tenacity import retry, stop_after_attempt, stop_after_delay, wait_random
+from torch.hub import download_url_to_file
+
+from cccv.config import BaseConfig
+
+if getattr(sys, "frozen", False):
+    # frozen
+    _IS_FROZEN_ = True
+    CACHE_PATH = Path(sys.executable).parent.absolute() / "cache_models"
+else:
+    # unfrozen
+    _IS_FROZEN_ = False
+    CACHE_PATH = Path(__file__).resolve().parent.parent.absolute() / "cache_models"
+
+
+CCCV_CACHE_MODEL_DIR = os.environ.get("CCCV_CACHE_MODEL_DIR", str(CACHE_PATH))
+
+CCCV_REMOTE_MODEL_ZOO = os.environ.get(
+    "CCCV_REMOTE_MODEL_ZOO", "https://github.com/EutropicAI/cccv/releases/download/model_zoo/"
+)
+
+
+def get_cache_dir(model_dir: Optional[Union[Path, str]] = None) -> Path:
+    if model_dir is None or str(model_dir) == "":
+        model_dir = str(CCCV_CACHE_MODEL_DIR)
+        print(
+            f"[CCCV] Using default cache model path {model_dir}, override it by setting environment variable CCCV_CACHE_MODEL_DIR"
+        )
+    if not os.path.exists(model_dir):
+        os.makedirs(model_dir)
+    return Path(model_dir)
+
+
+def get_file_sha256(file_path: Union[Path, str], blocksize: int = 1 << 20) -> str:
+    sha256 = hashlib.sha256()
+    with open(file_path, "rb") as f:
+        while True:
+            data = f.read(blocksize)
+            if not data:
+                break
+            sha256.update(data)
+    return sha256.hexdigest()
+
+
+def load_file_from_url(
+    config: BaseConfig,
+    force_download: bool = False,
+    progress: bool = True,
+    model_dir: Optional[Union[Path, str]] = None,
+    gh_proxy: Optional[str] = None,
+    **kwargs: Any,
+) -> Path:
+    """
+    Load file form http url, will download models if necessary.
+
+    Reference: https://github.com/1adrianb/face-alignment/blob/master/face_alignment/utils.py
+
+    :param config: The config object.
+    :param force_download: Whether to force download the file.
+    :param progress: Whether to show the download progress.
+    :param model_dir: The path to save the downloaded model. Should be a full path. If None, use default cache path.
+    :param gh_proxy: The proxy for downloading from github release. Example: https://github.abskoop.workers.dev/
+    :return:
+    """
+    model_dir = get_cache_dir(model_dir)
+    cached_file_path = model_dir / config.name
+
+    if config.url is not None:
+        _url: str = str(config.url)
+    else:
+        remote_zoo = CCCV_REMOTE_MODEL_ZOO
+        print(
+            f"[CCCV] Fetching models from {remote_zoo}, override it by setting environment variable CCCV_REMOTE_MODEL_ZOO"
+        )
+        if not remote_zoo.endswith("/"):
+            remote_zoo += "/"
+        _url = remote_zoo + config.name
+
+    _gh_proxy = gh_proxy
+    if _gh_proxy is not None and _url.startswith("https://github.com"):
+        if not _gh_proxy.endswith("/"):
+            _gh_proxy += "/"
+        _url = _gh_proxy + _url
+
+    if not cached_file_path.exists() or force_download:
+        if _gh_proxy is not None:
+            print(f"[CCCV] Using github proxy: {_gh_proxy}")
+        print(f"[CCCV] Downloading: {_url} to {cached_file_path}\n")
+
+        @retry(wait=wait_random(min=3, max=5), stop=stop_after_delay(10) | stop_after_attempt(30))
+        def _download() -> None:
+            try:
+                download_url_to_file(url=_url, dst=str(cached_file_path), hash_prefix=None, progress=progress)
+            except Exception as e:
+                warnings.warn(f"[CCCV] Download failed: {e}, retrying...", stacklevel=2)
+                raise e
+
+        _download()
+
+    if config.hash is not None:
+        get_hash = get_file_sha256(cached_file_path)
+        if get_hash != config.hash:
+            raise ValueError(
+                f"[CCCV] File {cached_file_path} hash mismatched with config hash {config.hash}, compare with {get_hash}"
+            )
+
+    return cached_file_path
+
+
+def git_clone(git_url: str, model_dir: Optional[Union[Path, str]] = None, **kwargs: Any) -> Path:
+    """
+    Clone or update a git repository. We suggest use HuggingFace repo instead of GitHub repo for larger models.
+
+    :param git_url: GitHub repository URL
+    :param model_dir: Directory to clone into
+    :param **kwargs: Additional git options (branch, commit_hash, etc.)
+    :return: Path to the cloned repository
+    """
+    if not shutil.which("git"):
+        warnings.warn(
+            "[CCCV] git is not installed or not in the system's PATH. "
+            "Please install git to use models from remote git repositories.",
+            stacklevel=2,
+        )
+
+    model_dir = get_cache_dir(model_dir)
+    # get repo name from url
+    repo_name = git_url.split("/")[-1].replace(".git", "")
+    clone_dir = model_dir / repo_name
+
+    if clone_dir.exists() and (clone_dir / ".git").exists():
+        print(f"[CCCV] Repository exists, updating: {clone_dir}")
+        subprocess.run(["git", "-C", str(clone_dir), "pull"], check=True)
+
+        # if branch or commit_hash is specified, checkout to that
+        if "branch" in kwargs:
+            subprocess.run(["git", "-C", str(clone_dir), "checkout", kwargs["branch"]], check=True)
+        if "commit_hash" in kwargs:
+            subprocess.run(["git", "-C", str(clone_dir), "reset", "--hard", kwargs["commit_hash"]], check=True)
+    else:
+        # clone the repo if not exists
+        print(f"[CCCV] Cloning repository: {git_url} -> {clone_dir}")
+        command = ["git", "clone", git_url, str(clone_dir)]
+
+        if "branch" in kwargs:
+            command.extend(["--branch", kwargs["branch"]])
+
+        subprocess.run(command, check=True)
+
+        if "commit_hash" in kwargs:
+            subprocess.run(["git", "-C", str(clone_dir), "reset", "--hard", kwargs["commit_hash"]], check=True)
+
+    return clone_dir
+
+
+if __name__ == "__main__":
+    # get all model files sha256
+    for root, _, files in os.walk(get_cache_dir()):
+        for file in files:
+            if not file.endswith(".pth") and not file.endswith(".pt"):
+                continue
+            file_path = os.path.join(root, file)
+            name = os.path.basename(file_path)
+            print(f"[CCCV] {name}: {get_file_sha256(file_path)}")
diff --git a/example/register.py b/example/register.py
index 7cb8245..1b11aec 100644
--- a/example/register.py
+++ b/example/register.py
@@ -1,6 +1,6 @@
 from typing import Any
 
-from cccv import ArchType, AutoConfig, AutoModel, SRBaseModel
+from cccv import CONFIG_REGISTRY, MODEL_REGISTRY, ArchType, AutoModel, SRBaseModel
 from cccv.config import RealESRGANConfig
 
 # define your own config name and model name
@@ -17,11 +17,11 @@
     scale=2,
 )
 
-AutoConfig.register(cfg)
+CONFIG_REGISTRY.register(cfg)
 
 
 # extend from cccv.SRBaseModel then implement your own model
-@AutoModel.register(name=model_name)
+@MODEL_REGISTRY.register(name=model_name)
 class TESTMODEL(SRBaseModel):
     def load_model(self) -> Any:
         print("Override load_model function here")
diff --git a/example/remote.py b/example/remote.py
new file mode 100644
index 0000000..10fb070
--- /dev/null
+++ b/example/remote.py
@@ -0,0 +1,10 @@
+import cv2
+import numpy as np
+
+from cccv import AutoModel, SRBaseModel
+
+model: SRBaseModel = AutoModel.from_pretrained("https://github.com/EutropicAI/cccv_demo_remote_model")
+
+img = cv2.imdecode(np.fromfile("../assets/test.jpg", dtype=np.uint8), cv2.IMREAD_COLOR)
+img = model.inference_image(img)
+cv2.imwrite("../assets/test_remote_example_out.jpg", img)
diff --git a/tests/test_auto_class.py b/tests/test_auto_class.py
index 326c255..a63bfcc 100644
--- a/tests/test_auto_class.py
+++ b/tests/test_auto_class.py
@@ -1,8 +1,18 @@
 from typing import Any
 
-from cccv import ArchType, AutoConfig, AutoModel
+import cv2
+
+from cccv import CONFIG_REGISTRY, MODEL_REGISTRY, ArchType, AutoModel
 from cccv.config import RealESRGANConfig
 from cccv.model import SRBaseModel
+from tests.util import (
+    ASSETS_PATH,
+    CCCV_DEVICE,
+    CCCV_FP16,
+    CCCV_TILE,
+    calculate_image_similarity,
+    load_image,
+)
 
 
 def test_auto_class_register() -> None:
@@ -17,12 +27,26 @@ def test_auto_class_register() -> None:
         scale=2,
     )
 
-    AutoConfig.register(cfg)
+    CONFIG_REGISTRY.register(cfg)
 
-    @AutoModel.register(name=model_name)
+    @MODEL_REGISTRY.register(name=model_name)
     class TESTMODEL(SRBaseModel):
         def get_cfg(self) -> Any:
             return self.config
 
     model: TESTMODEL = AutoModel.from_pretrained(cfg_name)
     assert model.get_cfg() == cfg
+
+
+class Test_AutoModel:
+    def test_model_from_remote_repo(self) -> None:
+        model: SRBaseModel = AutoModel.from_pretrained(
+            "https://github.com/EutropicAI/cccv_demo_remote_model", device=CCCV_DEVICE, fp16=CCCV_FP16, tile=CCCV_TILE
+        )
+
+        img1 = load_image()
+        img2 = model.inference_image(img1)
+
+        cv2.imwrite(str(ASSETS_PATH / "test_remote_repo_test_out.jpg"), img2)
+
+        assert calculate_image_similarity(img1, img2)
diff --git a/tests/test_cache_models.py b/tests/test_remote.py
similarity index 71%
rename from tests/test_cache_models.py
rename to tests/test_remote.py
index 37c0be0..49c7ca4 100644
--- a/tests/test_cache_models.py
+++ b/tests/test_remote.py
@@ -1,5 +1,5 @@
 from cccv import CONFIG_REGISTRY, ConfigType
-from cccv.cache_models import load_file_from_url
+from cccv.util.remote import get_cache_dir, git_clone, load_file_from_url
 
 
 def test_cache_models() -> None:
@@ -17,3 +17,8 @@ def test_cache_models_with_gh_proxy() -> None:
         force_download=True,
         gh_proxy="https://github.abskoop.workers.dev",
     )
+
+
+def test_git_clone() -> None:
+    clone_dir = git_clone("https://github.com/EutropicAI/cccv_demo_remote_model")
+    assert clone_dir == get_cache_dir() / "cccv_demo_remote_model"
diff --git a/tests/test_tile.py b/tests/test_tile.py
index e0e4b6f..0fa37d1 100644
--- a/tests/test_tile.py
+++ b/tests/test_tile.py
@@ -6,8 +6,7 @@
 
 from cccv import AutoModel, ConfigType
 from cccv.model import SRBaseModel, tile_sr
-
-from .util import ASSETS_PATH, CCCV_DEVICE, calculate_image_similarity, compare_image_size, load_image
+from tests.util import ASSETS_PATH, CCCV_DEVICE, calculate_image_similarity, compare_image_size, load_image
 
 
 def test_tile_sr() -> None:
diff --git a/tests/test_util.py b/tests/test_util.py
index a767cef..fa9ff81 100644
--- a/tests/test_util.py
+++ b/tests/test_util.py
@@ -15,8 +15,7 @@
     resize,
     ssim_matlab,
 )
-
-from .util import calculate_image_similarity, load_image
+from tests.util import calculate_image_similarity, load_image
 
 
 def test_device() -> None: